The calculated approximation of a result which is usable even if input data may be incomplete or uncertain.
0
votes
1answer
37 views
Which prices to use to compute realized volatility?
For computation of realized volatility, especially range based volatility, deal prices are commonly used.
If Level I data available should the deals data still be used or another measures of spot ...
8
votes
0answers
87 views
rugarch: Joint estimation leads to different results
I want to fit an ARMA-GARCH model to my data using rugarch package in R.
First of all, I look at the acf and pacf:
...
2
votes
1answer
95 views
How does the CME set margin requirements on commodity Futures
I am trying to model margin requirements on various commodity futures, however it doesn't seem that the CME has released the formula they use to set these performance bonds. I am sure that they use ...
3
votes
2answers
180 views
Fitting distributions to financial data using volatility model to estimate VaR
I want to fit a distribution to my financial data using a volatility model to estimate the VaR. So in case of a normal distribution, this would be very easy, I assume the returns to follow a normal ...
6
votes
0answers
129 views
How to estimate the following model?
Suppose I have the following model:
$$r_t=\sigma_t * \epsilon_t$$
where $r_t$ is the return at time t, $\sigma_t$ is the volatility, the model used to model this volatility is an exponentially ...
3
votes
1answer
65 views
How to calculate tracking error given mismatches in available data
Apologies if this is an overly simple question. I have a series of stock returns, and I would like to estimate my portfolio's ex-ante tracking error versus the benchmark (S&P 500) given the ...
17
votes
2answers
706 views
Tools in R for estimating time-varying copulas?
Are there libraries in R for estimating time-varying joint distributions via copulas?
Hedibert Lopes has an excellent paper on the topic here. I know there is an existing packaged called copula but ...
4
votes
0answers
64 views
Estimation of ranks of log-returns via copula
I have successfully chosen and estimate a copula for the ranks of the log-returns of my actions. My question is, since I have worked with the ranks instead of directly the log-returns (in order to be ...
11
votes
3answers
692 views
How to detect regime change when estimating asset correlation from historical time series?
Suppose I have two asset time series, $X_t$ and $Y_t$, and I'm estimating their correlation from historical data. I'd like to apply some systematic criterion to estimate what time window I should use ...
7
votes
2answers
308 views
Fitting a generalized logistic distribution
I have a process that estimates the parameters for the following function using the NL2SOL algorithm.
$C-[\alpha+\frac{\beta-\alpha}{1+e^-\theta(y_t-\delta)} \vartriangle y_t]$
The process currently ...
2
votes
2answers
187 views
Should I use GARCH volatility or standard deviation in cross-sectional regression?
I want to do a cross-sectional study where the historical, medium-long run volatility of some return series (call it $R_t$) is included as a regressor. Which of the following two estimates of ...
3
votes
1answer
175 views
How do I estimate the parameters of an MA(q) process?
It is relatively easy to estimate the parameters of an autoregressive $AR(p)$ process. How do I do with a moving average $MA(q)$ process?
6
votes
1answer
301 views
What distribution should I apply to estimate the likelihood of extreme returns?
Say I have a limited sample, a month of daily returns, and I want to estimate the 99.5th percentile of the distribution of absolute daily returns.
Because the estimate will require extrapolation, I ...
8
votes
1answer
289 views
Musiela parameterization
I have a question regarding the proof of the Musiela parametrization for the dynamics of the forward rate curve. If $T$ is the maturity, $\tau=T-t$ is the time to maturity, and $dF(t,T)$ defines the ...
8
votes
3answers
286 views
How to account for market movement when some exchanges are closed?
Daily data, such as open and close prices, is often available for much longer periods than high-frequency data. However, whenever backtesting any strategy that examines instruments traded in different ...
17
votes
2answers
476 views
How are distributions for tail risk measures estimated in practice?
Let's say you want to calculate a VaR for a portfolio of 1000 stocks. You're really only interested in the left tail, so do you use the whole set of returns to estimate mean, variance, skew, and shape ...
6
votes
1answer
130 views
What tradeoff is there to using an accurate estimate with a large confidence interval?
I am working on calibrating a Heston model from simulated historical stock data.
After obtaining an accurate estimate of the model parameters I found very large 95% confidence intervals for these ...
2
votes
1answer
99 views
How to reconstruct a discontinued economic time series such as the Fed's CP rate?
The old 3-Month Commercial Paper Rate (CP3M) on FRED was discontinued in 1997. I would like to reconstruct this series in a reasonable fashion, so I can use it to analyze more recent events.
I was ...
4
votes
2answers
1k views
How can I estimate the degrees of freedom for a Student's T distribution?
I am doing research estimating the value at risk for non-normally distributed assets. I need help in the process of estimating the parameters of Student's t distribution and which method to use. I ...
6
votes
2answers
302 views
Efficiency vs. Robustness - To use a constant or not in single factor time-series regression?
Arbitrage pricing theory states that expected returns for a security are linear combination of exposures to risk factors and the returns on these risk factors. Betas, or the exposures of the security ...
13
votes
5answers
895 views
How to estimate the probability of drawdown / ruin?
A fairly naive approach to estimate the probability of drawdown / ruin is to calculate the probabilities of all the permutations of your sample returns, keeping track of those that hit your drawdown / ...
11
votes
3answers
1k views
What methods do you use to improve expected return estimates when constructing a portfolio in a mean-variance framework?
One of the main problems when trying to apply mean-variance portfolio optimization in practice is its high input sensitivity. As can be seen in (Chopra, 1993) using historical values to estimate ...
